The past ten years of research had produced a variety of models for managing flexible loads, paving the way for addressing congestion in the grid by enabling a more efficient dynamic pricing of electricity. However, real change has been hard to come by in practice. The goal of this talk is to review such models, highlighting the difference between distributed algorithms, that seek to decompose the problem, and aggregate representations that map large populations of flexible loads onto spinning reserves. The objective is to highlight the challenges that exist in transforming and remaining compatible with established retail and wholesale market practices and legacy systems and how new abstractions may be necessary to rip the benefits of flexible load.

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